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Wednesday, 12 February 2025

Build awesome datasets for video generation

Hugging Face 1 year ago 43

Developers have released open-source tooling for building video generation datasets, including scripts for acquiring videos, filtering by watermarks and aesthetic quality, and automatically captioning frames. The filtering pipeline demonstrated that a watermark detection threshold of 0.1 was too strict, retaining only 47 videos from 1,493 originals, while an aesthetic score threshold above 5.5 also discarded usable content. The toolkit enables communities to create custom video datasets for fine-tuning models on specific effects, as shown by datasets built for crushing and cakifying objects.

From Chunks to Blocks: Accelerating Uploads and Downloads on the Hub

Hugging Face 1 year ago 47

Hugging Face's Xet team implemented a block-based deduplication system using content-defined chunking to accelerate file uploads and downloads on its model hub. For a 191GB repository of quantized model variants, the system reduced stored size to 97GB and cut upload time from 509 minutes to 258 minutes at 50MB/s, roughly a 2x speedup. The approach bundles chunks into 64MB blocks and uses key chunks as an index to avoid making millions of individual network requests, enabling faster iteration for AI builders uploading and downloading large files.

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